Parametric Design of Ethnic Patterns: Algorithmic Generation of Cultural Symbol Weaving Patterns

Under the impact of globalization and digital technology, the preservation of traditional ethnic patterns faces dual challenges in generation efficiency and cultural fidelity. This study proposes an interdisciplinary framework integrating semiotics, anthropology, and computational design to realize the algorithmic generation of ethnic cultural weaving patterns through parametric modeling. Taking Miao embroidery and Tibetan bajixiang as representative cases, a layered parametric extraction model (LPEM) is established and coupled with a fractal adaptive model (FAM) and a topology weaving rule model (TWRM) to transform geometric characteristics, color semantics, and symbolic constraints into computable design parameters. Experimental results demonstrate that the proposed method improves generation efficiency by approximately 760 times while maintaining high cultural fidelity, achieving a structural similarity of SSIM ≥0.86 and cultural acceptance above 85%. Furthermore, the flexible symbolic system of Miao embroidery exhibits greater algorithmic adaptability than the more rigid Tibetan religious pattern system, revealing the influence of cultural characteristics on computational optimization and parameter constraints. Beyond digital preservation of cultural heritage, the proposed framework establishes a generalized strategy for fractal geometry construction, topology-aware parametric modeling, and hierarchical pattern synthesis. These capabilities provide methodological references for the computational design of complex functional surfaces and periodic structures, with potential applications in electromagnetic wave manipulation, antenna geometry optimization, metasurface configuration, and intelligent electromagnetic structure generation.